DBMS > Interbase vs. Kinetica vs. Lovefield vs. Tkrzw

System Properties Comparison Interbase vs. Kinetica vs. Lovefield vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

Light-weight proven RDBMS

originally from Borland

Fully vectorized database across both GPUs and CPUs

Embeddable relational database for web apps written in pure JavaScript

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

www.embarcadero.com/products/interbase

www.kinetica.com

google.github.io/lovefield

dbmx.net/tkrzw

Technical documentation

docs.embarcadero.com/products/interbase

docs.kinetica.com

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Embarcadero

Kinetica

Google

Mikio Hirabayashi

Initial release

1984

2012

2014

2020

Current release

InterBase 2020, December 2019

7.1, August 2021

2.1.12, February 2017

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

JavaScript

C++

Server operating systems

Android
iOS
Linux
OS X
Windows

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

C++
Java
JavaScript (Node.js)
Python

JavaScript

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Interbase Change Views

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

using MemoryDB

yes

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

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